Electronically steered directive antenna arrays according to the known art use a technique known as digital beamforming. In digital beamforming, a plurality of signal waveforms N, which are to be transmitted, are represented by sequences of numerical samples, with the aid of Analog-to-Digital (AtoD) convertors, if necessary. In general the complex number sequences are applied to the inputs of a numerical processor known as a digital beamforming network. The digital beamforming network computes a number M of numerical output sequences corresponding to the number of elements in an antenna array that have to be driven. The general complex output sequences are converted to analog waveforms with the aid of Digital-to-Analog (DtoA) convertors for modulating a radio frequency carrier using, for example, a quadrature modulator of a known type. The modulated radio frequency waves are then amplified for transmission by respective antenna elements. This prior art digital beamforming network effectively performs a multiplication of a complex vector of N inputs with an MxN complex matrix of coefficients to form a complex vector of M outputs, for each time sample of the input signals.
A prior art digital beamforming network is illustrated in FIG. 1. Information signals, which may be analog signals such as speech, are converted to digital signals using AtoD convertors 10. The output signals from the AtoD converter 10 may, for example, be PCM signals of 8 kilosamples per second of 16-bit digitized samples.
The total bit rate of 128 Kilobits/sec is usually considered excessive for transmission of digital speech over radio links. As a result, an encoder 11, which may be a Residually Excited Linear Predictive encoder (RELP) or one of the other known forms such as Sub-band, CELP or VSELP is used to achieve significant compression of voice bit rates down to 8 kilobits per second or even lower while preserving reasonable telephone quality. Such encoders remove as much of the natural redundancy from speech as possible making received quality more sensitive to bit errors. It is therefore common to expand the bitrate again by replacing some redundancy in the form of more intelligent error correction coding. The net data stream is then impressed on a radio wave for transmission using any of the known digital modulation techniques such as PSK, QPSK, Offset-QPSK, Pi/4-DQPSK, 16 QAM and so on. In PSK, the radio carrier is simply inverted in phase depending on whether the data bit being transmitted is a binary `1` or a `0`. The abrupt inversion of the phase gives rise to spectral spreading of the radio signal and potential interference with other radio channels. Thus, the prior art modulation comprises filtering of the digital waveform to round-off the transitions between `1` (+1) and `0` (-1). In extreme cases known as partial response signalling, over-filtering is used to reduce the amount of spectrum used by a signal for its transmission. Filtering is used to obtain desired characteristics in the spectral domain, but can be achieved either with spectral domain filters such as may be constructed with resistors, inductors and capacitors or may be achieved by processing in the time domain using time samples. An archetypical time-domain filter is known as the transversal filter or Finite Impulse Response (FIR) filter. Other prior art time domain filters are known as Infinite Impulse Response filters (IIR).
An FIR filter comprises one or more delay stages for delaying the signal to be filtered forming a tapped delay line. When signals are already in the form of sequential numerical waveform values, such a tapped delay line may be formed by storing samples sequentially in a digital memory device. Samples delayed by different amounts are then weighted and added to form the filtering characteristic. Such a filter, when employed to filter digital waveforms, generally produces several output values per input data bit so as to correctly represent the shape of the 1-0 transitions which are important in controlling the spectrum to the desired shape. These values are no longer +1 or -1, but any value in between. Thus, premodulation filtering has the effect of changing single-bit information values to a plurality of multi-digit values.
In prior art beamforming methods, the filtered, multi-valued modulation waveform is applied to a digital beamformer 13. The digital beamformer forms M differently complex-weighted combinations of the modulation waveforms, which when modulated on to an appropriate radio frequency carrier and applied to corresponding antenna array elements, will result in each modulated signal being radiated in a separate, desired direction. The in-general complex numerical outputs of the beamformer are DtoA converted using, for example, a DtoA convertor for the real component followed by a smoothing or anti-aliasing filter to produce a continuous waveform between samples, and a similar device for the imaginary part. The DtoA converted waveforms are known as I,Q waveforms, and are applied to an I,Q modulator (or quadrature modulator) which impresses the complex modulation on a desired radio carrier frequency. The DtoA conversions anti-aliasing filtering and I,Q modulator are represented by blocks 14 of FIG. 1.
The prior art beamformer thus forms M combinations of the N input signals' samples by means of an MxN matrix multiplication with a matrix of combining coefficients. For example, suppose M=320 and N=640; then for each input signal sample period, 204800 complex multiply-accumulate operations have to be performed. A typical coded digital speech signal may be represented by a modulation waveform of 10 KHz bandwidth, which, if sampled at 8 samples per cycle of bandwidth in order to accurately represent 1-0 transitions, leads to 80 k complex samples per second from each modulation waveform generator 12. Thus the number of complex operations per second that digital beamformer 13 must execute is 80000.times.204800=16,384,000,000.
Instruction execution speeds of digital signal processing devices are measured in Mega-Instructions Per Second or MIPS. Thus, 16384 MIPS of processing are required. A complex multiply-accumulate consists however of 4 real multiply-accumulates in which DSP power is normally measured. Thus, the number of real MIPS required is thus 65536, or with allowance for overhead, &gt;100,000.
A state of the art digital signal processor such as the Texas Instruments TMS32OC56 executes about 40 MIPS. Thus, 2500 devices are needed for the postulated 320-input, 640-output beamformer. This may also be expressed as 8 DSP's per voice channel. As state of the art DSPs are expensive, the use of 8 DSPs per voice channel raises the cost of providing communications infrastructure which is measured in terms of cost per installed voice channel.